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幼儿的结构生成:生产性句法指数的修订版

Young Children's Structure Production: A Revision of the Index of Productive Syntax.

作者信息

Altenberg Evelyn P, Roberts Jenny A, Scarborough Hollis S

机构信息

Department of Speech-Language-Hearing Sciences, Hofstra University, Hempstead, NY.

Haskins Laboratories, New Haven, CT.

出版信息

Lang Speech Hear Serv Sch. 2018 Oct 24;49(4):995-1008. doi: 10.1044/2018_LSHSS-17-0092.

DOI:10.1044/2018_LSHSS-17-0092
PMID:29978201
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6430505/
Abstract

PURPOSE

The Index of Productive Syntax (IPSyn; Scarborough, 1990) is widely used to measure syntax production in young children. The goal of this article is to promote greater clarity and consistency in machine and hand scoring by presenting a revised version of the IPSyn (IPSyn-R) and comparing it with the original IPSyn (IPSyn-O).

METHOD

Longitudinal syntax production in 10 30- and 42-month-old typically developing children drawn from the Child Language Data Exchange System (MacWhinney, 2000) Weismer corpus was examined, using both the IPSyn-O and the IPSyn-R.

RESULTS

The IPSyn-R provided nearly identical scores to the IPSyn-O with the exception of scores affected primarily by 1 modified noun phrase structure. Structures ranked as more advanced were produced less frequently. The results also reveal which of the IPSyn-R's 59 structures were most and least likely to be produced by this sample at these ages.

CONCLUSIONS

The qualitative and quantitative differences between the IPSyn-O and the IPSyn-R are relatively minor. The IPSyn-R can make it easier to score the IPSyn, both by clinicians and researchers, and facilitate the IPSyn's move to machine scoring of language samples.

摘要

目的

产出性句法指数(IPSyn;斯卡伯勒,1990)被广泛用于测量幼儿的句法产出。本文的目的是通过呈现IPSyn的修订版(IPSyn-R)并将其与原始的IPSyn(IPSyn-O)进行比较,以促进机器评分和人工评分的更高清晰度和一致性。

方法

使用IPSyn-O和IPSyn-R,对从儿童语言数据交换系统(麦克温尼,2000)韦斯默语料库中抽取的10名30个月和42个月大的典型发育儿童的纵向句法产出进行了研究。

结果

IPSyn-R给出的分数与IPSyn-O几乎相同,只有主要受1种修改后的名词短语结构影响的分数除外。被列为更高级的结构产出频率较低。结果还揭示了IPSyn-R的59种结构中,在这些年龄该样本最有可能和最不可能产出的结构。

结论

IPSyn-O和IPSyn-R之间的定性和定量差异相对较小。IPSyn-R可以使临床医生和研究人员更容易对IPSyn进行评分,并促进IPSyn向语言样本的机器评分发展。

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